Key messageCoronavirus disease 2019 and FMF could interact via pathological pathways; therefore, treatment should address both conditions.Dear Editor, Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). After transmission through inhaled droplets and aerosols, the virus enters the host cells by binding of its spike protein to the receptor for the angiotensin-converting enzyme 2 [The autoinflammatory disease familial Mediterranean fever (FMF) is caused by mutations within the pyrin-encoding Mediterranean fever gene. The activation of the pyrin inflammasome leads to dysregulated pro-inflammatory cytokine production and inflammation . It can The German guidelines recommend tocilizumab, but not anakinra, in severe COVID-19 pneumonia, as of May 2021 . HoweverThe patient was a 19-year-old female of Armenian origin, who was diagnosed with FMF and chronic kidney failure attributable to reflux nephropathy 16 years ago. The FMF attack frequency for this patient was zero to one episode per year under treatment. The patient received a kidney transplant 4 years ago and was immunosuppressed with prednisolone (5 mg/day), AZA (50 mg twice a day) and tacrolimus (2 mg twice a day). Proteinuria owing to chronic allograft nephropathy was present, although amyloidosis was ruled out in rectal biopsies that were carried out 15 and 7 years previously and in a renal allograft protocol biopsy that was carried out 1 year earlier. Colchicine treatment had occurred for 16 years and stopped 8 months before admission, owing to gastrointestinal side-effects. Anakinra had been used for 4 years because of colchicine-resistant FMF attacks.Six days before admission (day 0), an episode of self-limiting abdominal pain without fever occurred. Owing to persisting dizziness and the onset of diarrhoea and nausea, a SARS-CoV-2 rapid antigen test was performed on day 3; the result was positive. She was not vaccinated and stopped anakinra owing to safety concerns. After developing a sore throat and dry cough, the patient was hospitalized on day 6. Upon examination, she was without fever (36.8°C) or dyspnoea (oxygen saturation of 98%). A chest X-ray revealed developing COVID-19 pneumonia. The initial investigations revealed a CRP of 13.8 mg/dl and IL-6 of 0.066 ng/ml. Procalcitonin was normal (0.13 ng/ml). The SARS-CoV-2 PCR test was positive for the B.1.1.7 variant.Rheumatology Advances in Practice online). The laboratory results revealed a further elevation of CRP to 22.2 mg/dl and IL-6 to 1.016 ng/ml, while procalcitonin remained normal. Prednisolone was changed to dexamethasone, according to our standard operating procedures and guidelines [On the morning of day 9, a second episode of abdominal pain and fever (38.6°C) occurred, followed by a decline in oxygen saturation to 83% some hours later. For adequate oxygenation, an oxygen mask with a flow of 5 l/min was initiated. A chest CT protocol showed that the patient had progressive COVID-19 pneumonia (idelines . After aRheumatology Advances in Practice online).The investigations on day 11 revealed a decline in CRP to 13.7 mg/dl and an elevation of IL-6 to 13.835 ng/ml, which was most probably attributable to the saturation of the IL-6 receptors by tocilizumab; a consecutive decrease occurred in the following days [FMF and COVID-19 involve the activation of innate immune response mechanisms, and some of their clinical manifestations overlap, namely fever and abdominal pain. In contrast to COVID-19, FMF attacks are typically recurrent and are always self-limiting up to ∼72 h. In this case, the first episode of self-limiting abdominal pain (which was suggestive of FMF) occurred at the onset of COVID-19. A second episode of abdominal pain was followed by respiratory failure. This case is an addition to our understanding of how FMF and infectious diseases, such as COVID-19, interact if they occur in a patient simultaneously. It should be discussed whether the acquired infections are part of the pathogenesis of FMF. If so, therapy should also address the underlying causes. We used tocilizumab successfully to address both conditions.Funding: No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this manuscript.Disclosure statement: The authors have declared no conflicts of interest.Consent: Informed consent was provided for the publication of this manuscript.The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.Rheumatology Advances in Practice online.rkab097_Supplementary_DataClick here for additional data file.


PD-L1. The cytokine profile of gingival crevicular fluid (GCF) samples obtained from periodontitis patients was estimated by cytometric bead array. CD3+ lymphocytes isolated from the peripheral blood were sorted and characterized using immunomagnetic techniques. Cultured and expanded lymphocytes were treated with the GCF samples to induce T-cell exhaustion. Optimum concentrations of allicin were added to exhausted lymphocytes to compare the expression of TIM-3 and LAG-3 gene expression at baseline and post-treatment. Allicin was found to bind to the PD-L1 molecule as revealed by the in-silico experiment, which is possibly an inhibitory interaction although not proven. GCF from periodontitis patients had significantly higher concentrations of TNF-α, CCL2, IL-6, IFN-γ, and CXCL8 than controls. GCF treatment of CD3+ lymphocytes from the periodontitis patients significantly increased expression of T-cell exhaustion markers TIM-3 and LAG-3. Allicin administration with GCF treatment resulted in significant lowering of the expression of exhaustion markers. Allicin may exert an immunostimulatory role and reverse immune-destructive mechanisms such as T-cell exhaustion. We evaluated the role of allicin in periodontitis using an in silico and in vitro design. An in silico docking analysis was performed to assess the plausible interactions between allicin and  Periodontitis is a disease with global prevalence. It affects the gingival tissues and attachment apparatus of the teeth. Periodontitis manifests in the formation of periodontal pockets and abscesses. It leads to episodic pain and tooth mobility . The disPorphyromonas gingivalis, Tannerella forsythia and Treponema denticola in the dental plaque biofilm causes the movement of leukocytes into the gingival tissues to combat the infection. The initial inflammation in the gingiva is characterized by the abundant presence of polymorphonuclear leukocytes or neutrophils [A substantive body of research has investigated the pathogenesis of periodontitis to develop effective therapeutic strategies to cure the condition. Earlier research revealed the immunological characteristics of periodontitis lesions. A microbial challenge mounted by putative periodontal pathogens such as trophils . They artrophils . Both T trophils . These ctrophils . Clinicatrophils . As the trophils .PD-1), T-cell immunoglobulin and mucin-domain containing TIM-3, and lymphocyte-activation gene (LAG-3). This can cause inhibition of the cell signaling pathways that activate T cells [PD-1 pathway is upregulated in the T cells of mice with chronic cytomegalovirus infection [PD-1 pathway is regulated by the binding of PD-1 to the PD-L1 ligand. The interaction of programmed cell death ligand -1(PD-L1) with PD-1 triggers downstream signaling pathways that leads to T-cell exhaustion [LAG-3 and TIM-3 also are coexpressed and upregulated in T-cell exhaustion along with the activated PD-1 pathway. LAG-3 acts synergistically with PD-1, causing severe T-cell exhaustion. Inhibition of LAG-3 and TIM-3 markers quickly revives exhaustion of the affected T cells [T-cell exhaustion is a phenomenon that occurs in chronic conditions such as periodontal disease and cancer. A state of T-cell dysfunction occurs after chronic exposure of T cells to antigens . Classic T cells . Earliernfection . PD-1 isnfection . The PD-haustion . Other m T cells . Porphyromonas gingivalis could also account for the T-cell exhaustion phenomenon due to upregulation of PD-L1. Previous research indicated that Porphyromonas gingivalis infection of oral squamous cell carcinoma cell lines causes a significant PD-L1 increase [PD-1 and LAG-3 in the lesion environment [PD-1 has been reported in samples obtained from patients with periodontitis [PD-1 pathway checkpoints. Earlier research has shown three herb-derived molecules that show promise—curcumin from Curcuma longa, baicalin from the Chinese herb Scutellaria baicalensis, and the triterpenoid saponin platycodin-D from the roots of Platycodon grandiflorum. These herbs have traditionally been used in Chinese herbal medicine [PD-L1. Garlic possesses similar immunomodulatory properties and is far easier to source. The chemical allicin from garlic exerts immunostimulant activities [PD-1 pathway. This exploratory study was designed to examine whether allicin could inhibit PD-L1 at the in-silico level. We investigated the effects of allicin administration on T-cell exhaustion and revival. We also evaluated whether gingival crevicular fluid obtained from patients with periodontitis could cause dysfunction of T cells obtained from the same patients in an in vitro culture setting. In periodontitis, the cytokine milieu is possibly the main factor implicated in T-cell exhaustion. An increase in the counts of periodontal pathogens such as increase . A studyironment . A simildontitis . Plant-dmedicine . These htivities . The immtivities . It was tivities . AllicinPD-L1. The single-dimensional structure of allicin is depicted in PD-L1. We observed that allicin interacts with PD-L1 through hydrogen bonds and hydrophobic interactions. PD-L1 in various positional confirmations. At position 7, a negative binding energy of −7.10 kcal/mol could be elicited. This depicts a very high affinity and interaction energy between allicin and PD-L1. We concluded from the in-silico data that allicin could possibly be an inhibitor of PD-L1.An in-silico design was used to study the binding interaction between allicin and The present study had an in vitro component using GCF samples collected from five patients with periodontitis. These samples were used for cytokine profile analysis and addition to T-lymphocyte cultures for induction of T-cell dysfunction. The lymphocyte cultures that underwent GCF treatment were also expanded from CD3+ lymphocytes separated from blood samples obtained from the patients with periodontitis. Five systemically healthy subjects with healthy periodontal status were chosen as the control. GCF samples were obtained from the control for comparison of cytokine profile with the periodontally diseased GCF samples. The results of the study are presented in further sections.p < 0.05)  . Sorted CD3+ T lymphocytes obtained from the peripheral blood samples were maintained in culture and expanded. The cells were treated with different concentrations of allicin and incubated for 48 h A–J. The TIM-3 and LAG-3 increased significantly in CD3+ T cells in a dose-dependent and time-dependent manner (p < 0.05). The highest level of gene expression was in presence of 2 μL/mL of GCF after 48–72 h of the incubation  (Treatment with 2 μL/mL GCF of CD3+ T cells induced the highest levels of  < 0.05) .The present study explored the effect of allicin on T-cell dysfunction and activation. We sought to elucidate the possible host modulatory effects of allicin derived from garlic in the management of periodontitis. The choice of CD3+ lymphocytes was based on the fact that CD3+ cells depict a population helper and cytotoxic T cells, which are very critical in periodontitis pathogenesis. Moreover, the Th response is also largely dependent on T cells. It has been proven beyond doubt that antibody production by B cells is dependent on T-cell responses. Hence, we assessed the effect of allicin on the above cellsPD-1 pathway can result in T-cell exhaustion, characterized by T-cell dormancy and reduced immune response. For the in-silico analysis, a molecular docking study was performed to examine the interaction between the allicin and PD-L1 pathway. The results revealed that allicin is bound to PD-L1 with high affinity and could possibly cause inhibition of PD-L1 although not demonstrated in the present study. If further proven in an in vivo environment, this would translate to a blockade of the PD-1 checkpoint pathway and prevention of T-cell exhaustion. From this result, it can be extrapolated that allicin could possibly be a potent phytochemical inhibitor of T-cell exhaustion. Activation of the TIM3 and LAG3, in T cells following GCF treatment. These findings suggest that T-cell exposure to the GCF led to T-cell dysfunction.We conducted a wet lab assay to explore in vitro induction and reversal of T-cell dysfunction in periodontitis. GCF samples and CD3+ T cells were obtained from patients with periodontitis. T cells were expanded, cultured, and treated with the GCF samples of the periodontitis patients, and T-cell dysfunction was assessed. CD3+ T lymphocytes were obtained from the patients following immunosorting. CD3+ is a specific cell surface marker and a coreceptor of both helper T cells and cytotoxic T cells. GCF is an exudate that is produced in excess amounts during the pathogenesis of periodontal inflammation . It is aPD-1 is an inhibitory receptor subtype of the CD28 superfamily. It is upregulated on exhausted CD8 T cells during chronic LCMV infection. A blockade of this pathway can rejuvenate and restore CD8 T-cell function and enhance the resolution of the viral infection. PD-1 seems to act as a checkpoint molecule in T-cell exhaustion. TIM-3 and LAG-3 are considered markers of T-cell exhaustion. These surface molecules are coexpressed on exhausted T cells along with PD-1 [TIM-3 and LAG-3 to be positively overexpressed in T cells following GCF treatment. T-cell exhaustion is a cellular and molecular mechanism that occurs in many chronic and viral conditions. T-cell exhaustion is characterized by hierarchical loss cytotoxicity, mitosis, and IL-2 production, followed by the production of IFN-γ and TNF-α. Researchers have described T-cell exhaustion as a peripheral tolerance mechanism where T cells lose their phenotypic functions. During the exhaustion phenomenon, there is a characteristic upregulation of inhibitory receptors on T cells. A study of LCMV-infected mice revealed the significant role of inhibitory receptors following a blockade of the programmed death 1 (PD-1) pathway. PD-1 and its ligand play a pivotal role in this regard . PD-1 isPD-1-, TIM-3-, and LAG-3-mediated cell signaling pathways can reverse T-cell exhaustion. Therapeutic strategies that modulate the PD-1 checkpoint have been proposed. Herbal extracts and herb-derived active molecules such as platycodin-D, baicalin, and curcumin are thought to modulate the PD-1 pathway and revive T-cell activity. Allicin  is a defense molecule derived from the herb garlic. In our study, T cells were treated with the GCF cytokine cocktail and allicin. We observed that allicin restored T-cell function significantly by downregulating the expression of TIM-3 and LAG-3 genes. Allicin had a significant effect on reviving T-cell dysfunction at a concentration of 25 μM after 48–96 h of incubation. This concentration was not cytotoxic to T cells as evidenced by the MTT cytotoxicity assay.A blockade of Allium Sativum L, commonly referred to as garlic, exhibits immunomodulatory properties. On tissue damage, the enzyme alliinase catalyzes the conversion of the amino acid alliin to the thiosulfinate allicin [κB activation, and thereby prevent liver damage [α secretion, and protects intestinal epithelial cells [ allicin . Decompo allicin . Allicin allicin . Earlierr damage . Previoual cells .Allicin is easily synthesized as its natural source is abundant. Allicin may have applications as a host modulatory strategy in periodontal therapy where inflammation, a diminished immune response, dysregulated oxidant–antioxidant mechanisms, and T-cell exhaustion have a role to play. Allicin could be a candidate for addition to mouthwashes, toothpaste, and intrapocket delivery systems to exert topical effects. Further studies on animal models of ligature-induced periodontitis may help develop a fuller picture of allicin’s ability to reverse T-cell exhaustion. Research in this regard can unearth further applications of allicin as a perioceutical agent in the management of destructive periodontal disease.Scientific research (IRB), College of Dentistry, Jazan University approved the study (Reference no.CODJU-19233). The study was comprised of an in silico component performed by a trained team of bioinformatic specialists, while the in vitro studies were carried out in the molecular biology laboratory. The crystal structure of the programmed cell death ligand 1(PD-L1) intended as the receptor binding to the allicin ligand was used in the docking study (5NIU). The protein was processed by eliminating certain specific ligands. PyRx virtual screening software  was used to prepare for docking. The protein was further processed into a PDBQT file format to facilitate readability in the AutoDock software . The three-dimensional configuration of allicin was extracted from the PUBCHEM database. The ligand was prepared for the docking process by the addition of charges and optimization using the universal force field. The ligand structure was converted into the PDBQT file format to facilitate readability in the AutoDock software. The one-dimensional structure of the allicin ligand is depicted in Written informed consent was obtained from all patients who participated in the study. Five patients who were diagnosed with periodontitis after intraoral examination and periodontal charting were enrolled in the study. The diagnosis of periodontitis was made according to the 2018 World Workshop classification of periodontal diseases, which is the most updated classification system available . An addig and stored at −80 degrees centigrade until further analysis. The same sampling protocol was followed for the systemically and periodontally healthy subjects to obtain pooled GCF samples from 4 periodontally healthy sites. The GCF samples obtained from the control subjects were used for cytokine analysis to compare the levels of cytokines in the GCF samples of periodontitis patients. No further analysis was conducted on the samples from the control subjects. One portion of the sampled GCF from each periodontitis patient was used to analyze the cytokine profile, while the other portion was used for in vitro lymphocyte treatment to induce T-cell dysfunction. A 5 mL blood sample was collected from each periodontitis patient from the antecubital vein using a sterile aseptic protocol. The blood sample was immediately transported to the molecular biology facility for isolation of CD3 + cell isolation and culture of the cells. The GCF sample collected from a periodontitis patient was used to induce T-cell dysfunction in the T cells obtained and cultured from the same patient to simulate a clinical scenario in an in vitro setting.After a thorough clinical examination, the patients were seated upright in the dental chair with good illumination. GCF was sampled from the deepest periodontal pocket in each quadrant of the patient’s mouth using microcapillary pipettes using a standard protocol . IsolatiTM human essential immune response panel (13-plex)  was used for cytokine detection . The experimental protocol followed the manufacturer’s instructions. In total, 25 μL of the GCF samples was incubated for 2 h with the microbeads. The detection antibodies were added to the tests after incubation and incubated for 30 min. Following incubation, the samples were washed with the wash buffer. The samples were then centrifuged at 2000 rpm for 5 min. Following supernatant elimination, the pellet was resuspended in a 200 μL sheath fluid. The samples were acquired using a flow cytometer  and analyzed using LEGENDplexTM data analysis software .To determine the levels of the cytokines in the GCF samples, a cytometric bead array was performed. The LEGENDplexTotal CD3+ T lymphocytes were isolated with magnetic cell sorting using a human-specific CD3+ microbead kit  from restored peripheral blood mononuclear cells (PBMCs). Sorted CD3+ T cells were subject to culture using TexMACS immune cell-culturing medium . Activation and expansion was induced by using human T-cell activation/expansion kit  with addition of 100 U/mL of IL-2 .3 cells per well and incubated for 24 h. The adhered cells were treated with complete medium (DMEM + 10% FBS) mixed with allicin  of various concentrations ranging between 0.5 and 250 µM. The samples were incubated for 48 h. After incubation, MTT solution (0.5 mg/mL)  was added to each well and incubated for four hours at 37 °C. Postincubation, the medium was removed, and 100 µL dimethyl sulfoxide (DMSO)  was added to each well. Multiskan FC spectrophotometer  was used to measure the absorbance at 570 nm.Cell viability was measured using an MTT assay. The cells were seeded into 96-well plates  at a density of 5 × 10CD3+ T cells were cultured in a 24-well plate  with a density of approximately 1 million cells/well. Cells were treated with different volumes of GCF  and were incubated for 24, 48, 72, 96, and 120 h. Similarly, T cells were treated with different concentrations  of allicin along with 2 µL/mL GCF for the same time points. T cells without GCF treatment were regarded as controls.The total RNA was extracted from treated T cells with GeneJet purification columns . High-capacity cDNA reverse-transcription kit  was used for conversion of 1 μg of total RNA into cDNA. Quantitative analyses of gene expressions were conducted by using the SYBRGreen PCR master mix  on QuantStudio 5 real-time PCR system . Respective primers  were used for the analysis. The primer sequence of the housekeeping GAPDH gene, TIM-3, and LAG-3 are presented in p-value of less than 0.05, and a p-value less than 0.01 was interpreted as highly significant.The experiments were performed in triplicates and the obtained results are presented as mean ± standard deviation. Each experimental group was individually compared with the control group, and the data were analyzed using an unpaired t-test (two-tailed) on GraphPad Prism 8 software . The level of significance was set at a This study set out to examine whether allicin derived from the herb garlic could reverse T-cell dysfunction. In our study, allicin bound and inhibited PD-L1 in the in silico model. Allicin administration alleviated T-cell dysfunction by downregulating the TIM-3 and LAG-3 genes in a dose-dependent and time-dependent manner. Allicin may have beneficial biological effects by reversing T-cell dysfunction in chronic conditions. It may have clinical applications in treating T-cell-mediated diseases and chronic inflammatory disorders.


N = 44) were used to train a model. The presence of SRC became an optimal decision parameter for pathology alone (AUC = 0.78). Analysis of differentially expressed genes (DEGs) for the prediction of genomic markers showed that C-X-C motif chemokine ligand 11 (CXCL11) was high in responders (P < 0.001). Immunohistochemistry (IHC) was performed to verify its potential as a biomarker. IHC revealed that the expression of CXCL11 was associated with responsiveness (P = 0.003). The response prediction model was trained by integrating the results of the analysis of pathological factors and RNA sequencing (RNA-seq). When trained with the C5.0 decision tree model, the categorical level of the expression of CXCL11, a single variable, was shown to be the best model (AUC = 0.812). The AUC of the model trained with the random forest was 0.944. Survival analysis revealed that the C5.0-trained model  and the random forest-trained model  predicted prognosis more accurately than the PD-L1 test .The identification of predictive biomarkers or models is necessary for the selection of patients who might benefit the most from immunotherapy. Seven histological features  detected in surgically resected tissues ( CXCL11 was associated with a strong positive response to the drugs. The researchers used these and other biomarker data to build a model for selecting appropriate candidates for immunotherapy. Further research will refine this initial biomarker list for gastric cancer and help improve the model.A prediction model that identifies patients with gastric cancer who are likely to respond well to immunotherapy has been developed by researchers in South Korea. Hansoo Park at the Gwangju Institute of Science and Technology and co-workers identified several biomarkers in gastric cancer tissues that were associated with how well patients may respond to immunotherapy treatment. They found that patients with malignant cells known as signet ring cells were least likely to respond well to immune checkpoint inhibitor drugs. Conversely, high expression levels of a gene called  Recent studies have suggested the tumor mutational burden as a predictive factor of survival in patients with gastric cancer following treatment with ICIs5. Microsatellite instability-high (MSI-H) and Epstein-Barr virus (EBV), for which testing is currently available in most clinical settings, have been reported as good markers for predicting the responsiveness of gastric cancer to immunotherapeutic agents4. Moreover, MSI-H has also been reported as an indicator of a high mutational load. Several reports have shown that an abundance of tumor-infiltrating lymphocytes (TILs), such as CD3 or CD8, is associated with a good prognosis9. Based on these findings, pembrolizumab was approved in the United States for previously treated patients with advanced gastric cancer expressing a combined positive score (CPS) ≥ 1% on the programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) test11. However, it exhibited conflicting results in numerous studies evaluating the relationship between the expression of PD-L1 and response to ICIs. Different trials with pembrolizumab or nivolumab have demonstrated a rather wide range of response rates (10–26%) in patients with metastatic gastric cancer who are administered salvage therapy without a selective biomarker or PD-L1 positivity13. Cottrell et al. evaluated the histological features of non–small cell lung carcinoma using anti-PD-L1-mediated “immune regression and proposed associated immune-related pathologic response” (irPR) criteria in routine hematoxylin and eosin (H&E)-stained slides and correlated them with those of the residual viable tumor14. Similarly, the irPR score was shown to be significant in the overall response rate and overall survival of patients with melanoma15. However, this approach requires a biopsy during treatment, and gastric cancer is histologically different from lung cancer and melanoma.The use of immune checkpoint inhibitors (ICIs) is an emerging treatment option for a variety of solid tumors. For instance, ICIs have demonstrated good therapeutic efficacy in patients with advanced gastric cancer. To improve the efficacy of anti-programmed death-ligand 1 (anti-PD-L1) therapy in advanced gastric cancer, it is necessary to identify precise predictive biomarkers or models for the optimized selection of patients with gastric cancer who might benefit the most from immunotherapyIn this study, we trained an optimal decision model to predict the response to PD-L1 inhibitors using histological features from surgical specimens of gastric cancer and validated the accuracy of the model in biopsy tissues. In addition, we searched for differentially expressed genes (DEGs) using RNA sequencing to identify markers that could support the PD-L1 IHC test. We also performed IHC to verify the usefulness of the identified genes as biomarkers. Finally, we combined these histological characteristics and the results of genomic analysis to construct an optimal prediction model for the efficacy of PD-L1 inhibitors.16. Patients who achieved partial response and complete response were classified as responders (R). Patients who achieved progressive disease and stable disease were classified as nonresponders (NR). This study was approved by the Institutional Review Board of Gwangju Institute Science and Technology (IRB number: 20200108-BR-50-04-02). All patients provided written informed consent before enrollment.All patients recruited for this study were referred by the research team of Professor Jeeyun Lee, Division of Hematology-Oncology, Samsung Medical Center. Enrolled patients received consultation at the Hematology-Oncology Unit of the Samsung Medical Center. Patients enrolled in this study had to meet the following criteria: (1) histologically confirmed diagnosis of gastric or gastroesophageal junction adenocarcinoma, (2) age of at least 19 y, (3) previous failure of at least one line of chemotherapy that included platinum/fluoropyrimidine, (4) willingness to undergo a procedure to obtain fresh-frozen tissue within 42 d of treatment initiation for biomarker analysis, (5) adequate organ function per protocol, (6) at least one measurable lesion according to the Response Evaluation Criteria in Solid Tumors (RECIST) v.1.124, and (7) Eastern Cooperative Oncology Group performance status of 0 or 1. All patients were naive to anti-PD-1, anti-PD-L1, or anti-PD-L2 antibodies. Clinical information was collected from the electronic medical records maintained at the electronic database of the hospital. All tumor tissues used for pathology and genomic analyses in this study were obtained anytime between day 42 and day 1 prior to the initiation of study treatment. The responsiveness to ICIs was evaluated using the Response Evaluation Criteria in Solid Tumors v1.1N = 44) and biopsied tissues (N = 47) for each case were independently assessed by two pathologists (M-GN and K-HL) to evaluate, select, and score the histopathological features (presence of signet ring cell (SRC) component, histologic grade, presence of fibrous stroma, presence of myxoid stroma, grade of tumor-infiltrating lymphocytes (TILs), presence of neutrophil infiltration, presence of tumor necrosis, presence of tertiary lymphoid follicles, and presence of epithelial ulceration  tissues from 100 patients with histologically confirmed gastric adenocarcinoma treated with pembrolizumab were provided by the research team of Professor Lee. We received 10 slides from a single representative section for each patient. After excluding nine patient tissues that could not be utilized due to slide damage, 44 surgically obtained large tissue specimens and 47 small tissue specimens obtained by endoscopy or needle biopsy were used to train the predictive model. H&E slides from surgical specimens . TILs whttps://www.ebi.ac.uk/ena/data/view/PRJEB25780). The deposited data featured 45 patients, and all clinical data were provided by the research team of Professor Lee. The method of RNA sequencing has been previously described4. Alignment, annotation, and quality control were carried out via the RNA sequencing (RNA-seq) workflow using the bcbio-nextgen bioinformatics framework (version 1.2.4) (https://github.com/bcbio/bcbio-nextgen)18. In brief, raw reads were aligned to the GRCh38 (hg38) version of the human reference genome using STAR version 2.6.1d19. MultiQC was then used for quality control and assurance analysis of the resulting bam file by comparison to metrics gathered from bcbio-nextgen, samtools20, and fastqc21. Quantitated reads were assigned to genes (features) annotated in Ensembl and counted with featureCounts23. As recommended by the developers of the bcbio-nextgen pipeline, we loaded the gene-level counts.csv.gz and the metadata.csv.gz and used DESeq2 for gene-level analysis (https://github.com/bcbio/bcbio-nextgen/blob/master/docs/contents/bulk_rnaseq.md)24. Gene set enrichment analysis (GSEA) was performed using Hallmark gene set v7.2 in version 4.0.3 of GSEA software (Broad)26. The number of permutations was set to 1000, and the chosen permutation type was phenotype. Results with a P value and FDR less than 0.05 were considered significant. Similarly, gene set variation analysis (GSVA) was performed using Hallmark gene set v7.2 with the GSVA package in the R-4.0.2 program27. In the GSVA package, the “ssgsea” method was selected and analyzed with a minimum size of 10 and a maximum size of 500.The data of all used RNA sequencing FASTQ files had already been deposited as PRJEB25780 in the European Nucleotide Archive (N = 91) received from the pathology test described above. All immunostained slides were individually evaluated twice by two pathologists (M-GN and K-HL) blinded to the clinical details. The cell membrane and cytoplasm of tumor cells were evaluated for the expression of CXCL11. Lymphocytes were stained to evaluate inflammatory cells infiltrating the tumor or present around the tumor. In addition, the interstitial and blood vessels around the tumor were examined. The intensity of expression was graded using a 3-tier system as strong (3+), moderate (2+), or weak (1+). The extent of expression was evaluated using a 3-tier system with cutoffs of 5 and 50%. This intensity and extent criteria were applied equally to the tumor cell membrane, tumor cell cytoplasm, TILs, and interstitial and blood vessels around tumors. Clinical information as well as PD-L1 (IHC) combined positive score (CPS) results, EBV (in situ hybridization) results, and MSI (IHC) results were received from the research team of Professor Lee. The PD-L1 (IHC) test was performed at Samsung Hospital as follows. Tissue sections were freshly cut to slices of 4 μm thickness, mounted onto Fisherbrand Superfrost Plus Microscope Slides (Thermo Fisher), and then dried at 60 °C for 1 h. IHC staining was carried out on a Dako Autostainer Link 48 system (Agilent Technologies) using a Dako PD-L1 IHC 22C3 pharmDx kit (Agilent Technologies) with an EnVision FLEX visualization system and counterstained with hematoxylin according to the manufacturer’s instructions. PD-L1 protein expression was determined using CPS as follows: the number of PD-L1-stained cells  divided by the total number of viable tumor cells multiplied by 100. The specimen was considered to have PD-L1 expression if CPS ≥ 1. The MSI status was determined at the Samsung Medical Center by IHC for both MLH1  and MSH2  in FFPE tissue sections and polymerase chain reaction (PCR) analysis of 5 markers with mononucleotide repeats , as previously described28. The EBV status was determined at Samsung Medical Center by EBV-encoded small RNA (EBER) in situ hybridization using standard protocols29.We used the C-X-C motif chemokine ligand 11 (CXCL11) primary antibody  at a dilution of 1:400 using an antibody diluent  for immunohistochemical analysis. According to the antibody datasheet, two clear cell renal cell carcinoma tissues were used as controls to validate the results. Moreover, normal gastric tissue was used as a negative control for comparison with gastric cancer tissue. After determining the staining conditions, IHC staining was performed on all nonstained slides  was used. Survival analyses were performed utilizing the survival R package. Kaplan–Meier survival curves were used to estimate the patterns of progression-free survival (PFS) and overall survival (OS). For Kaplan–Meier curve survival analysis, a log-rank test  was used to compare survival curves. In the analysis of differentially expressed genes (DEGs), the fold change value was set to be less than 2, and the P value was set to be greater than 0.05. The collective 2-sided binomial Mann–Whitney–Wilcoxon test was used to compare differences between 2 groups. Linear correlations were determined using the Pearson correlation method. To classify the expression of each gene into a binary category, the ROC function of Epi in the R package was used. P values less than 0.05 were considered significant.Statistical analysis was performed using IBM SPSS Statistics for Windows version 25.0  and the R-4.0.2 program for Mac OS. The chi-squared and Fisher’s exact tests were used to correlate the histopathologic features of pathological tissues and responsiveness using SPSS statistics. Heatmap representation of the exploration and validation cohorts was performed according to the study by Stein et al.carat R package was used in the model to predict responders versus nonresponders. We used the C5.0 decision tree model30 and random forest for classification31. To estimate the ‘out-of-bag’ area under the curve (AUC), a 10-fold cross-validation was repeated 500 times, and the best model was extracted. The winnow parameter was set to “TRUE”; therefore, we tried to prevent overfitting by measuring whether the field was useful in advance for the input field and then excluding it if it was not useful and modeling it. For random forest training, we used parameters that generated an ensemble of 500 trees. Repeated 10-fold CV was used to most accurately compare model performance. To define the optimal number of variables, a grid with mtry parameters of 1, 2, 3, 4, 8, and 16 was created. The roc function of the R package proc was used to compare the performance of each model.The All patients were Korean. The median age of the patients was 58 y , and the majority were men (57.8%) Table . Poorly P < 0.001 and P = 0.042, respectively)    and overall survival (OS) (log-rank P = 0.001) in patients without SRC than in those with SRC  Fig. . We obse05) Fig. . Similar05) Fig. . We acco.78 Fig. , d. SurvSRC Fig. , f. To vP = 0.283)   or OS (log-rank P = 0.216)  and OS (log-rank P = 0.001)  Fig. . In cont41) Fig. . It shou16) Fig. , c. Howe01) Fig. d, e. Fol01) Fig. .P = 0.079 and FDR q-value = 1.0) and interferon-α response set  were enriched in responders   than CD274 (P = 0.002), the gene encoding the PD-L1 protein   and OS (log-rank P = 0.018)  test. We found that 01) Fig. . Interesein Fig. . In addiers Fig. . We furt43) Fig. . Receive788 Fig. . Likewis829 Fig. . To use 18) Fig. , h.Fig. CXCL11 at the transcript level, we performed IHC to reveal its protein expression in tissues. Accordingly, we evaluated the expression of CXCL11 in all stained cells and determined its location, intensity, and extent    but not OS (log-rank P = 0.072)  Fig. . Logisti01) Fig. . Therefo72) Fig. , e.Fig. P = 0.013), CD274 , CXCL11 , PD-L1 , and MSI  were significantly associated with responsiveness , TILs (H&E), and MSI (IHC) were important variables in the random forest-trained model  categorical variable revealed a more significant difference for both PFS (log-rank P = 0.01) and OS (log-rank P = 0.012) between responders and nonresponders in the model trained with the C5.0 decision tree compared with the results predicted with the PD-L1 (IHC) test    gastric cancer be actively considered for pembrolizumab monotherapy, similar to those with MSI-H tumors. However, research on histopathological biomarkers other than genetic variations has been insufficient. In many cases, patients with gastric cancer are diagnosed through endoscopic biopsy. As the biopsy tissue is markedly smaller than the surgically excised tissue, a single PD-L1 IHC test alone would not provide a sufficiently accurate result to predict the efficacy of a drug. Thus, the prediction of nonresponders based only on histological features prior to the PD-L1 IHC test might prevent unnecessary testing and treatment. In particular, we sought to identify histological features that pathologists could easily identify in small biopsy tissues. For instance, the presence of SRC is considered a representative histological finding in gastric cancer with poor differentiation and has been linked to a poor prognosis32. In this study, the presence of SRC was shown to be important in predicting the efficacy of ICIs. However, there have been few reports on the clinical impact of ICI markers on SRC in gastric cancer. Jin et al. reported the expression of PD-1, PD-L1, T cell infiltration, MSI, and EBV, as well as the relationship of each factor with survival, in 89 patients with advanced SRC carcinoma33. Although the patients in that study were not treated with ICIs, it was the only investigation reporting an association of SRC with PD-L1. PD-1, PD-L1, T cell infiltration, MSI, and EBV did not affect prognosis. In other words, the presence of SRC, which does not appear to be influenced by other factors, might be an independent variable in predicting prognosis. Therefore, the presence of SRC in nonresponders to ICIs  might be an important finding in our study. Importantly, our study provides the first evidence of a high nonresponse rate to pembrolizumab in SRC tumors. The presence of SRC and TILs in small biopsy tissues at the time of diagnosis by a pathologist could be used to predict responsiveness to ICIs. This result could be helpful even in a clinical environment where the latest molecular pathology diagnostic equipment might not be available.In this study, we analyzed a clinically annotated cohort of patients with advanced gastric cancer treated with anti-PD-L1 ICIs with available histopathology, RNA-seq, and IHC data. We analyzed each datum individually, as well as integrally. In their study, Kim et al showed that MSI-H and EBV (+) were reliable biomarkers for immunotherapy, as well as for PD-L1 IHCCXCL9/10/11-CXCR3 signaling pathway is known to primarily promote the chemotactic movement of CXCR3-activated immune cells into the tumor site for antitumor immunity34. Zhang et al. reported that CXCL11-CXCR3 upregulated the expression of PD-L1 by activating the STAT and PI3K-Akt signaling pathways in gastric cancer cells in vitro35. Genetic analysis of DEGs using RNA sequencing data has suggested the possibility of molecular markers and their usefulness in IHC settings. In this study, DEG analysis using RNA sequencing data revealed that the expression of CXCL11, CXCL9, and CXCL10 was significantly high in responders to ICIs   Fig. , consistCD274 gene and the PD-L1 (IHC) test was low (r2 = 0.202), as was the correlation between the expression of the CXCL11 gene and the IHC staining of CXCL11 (r2 = 0.107)  Fig. . This di18, we simultaneously performed analyses of alternative splicing, genetic variation, and structural variation. Briefly, after the sequencing results were arranged in STAR19, genetic variant calling was performed using the gatk-3.8 HaplotypeCaller36 followed by VEP37, while alternative splicing analysis was performed using rmats-4.1.038, and structural variation analysis was performed using arriba39. However, each analysis tool needed to be further validated so that the expected results would be consistent with the actual results, and thus, it was difficult to use these results in the current study. Further research on the results of each analysis tool is needed.Research using RNA-seq data allows the analysis of not only differentially expressed genes, as in this study, but also of alternative splicing, variants, structural variants, and neoantigens. As described above, while analyzing DEGs using the bcbio-nextgen bioinformatics framework (version 1.2.4)CXCL11 (RNA-seq) was the model with the best performance even when all decision trees with one variable were randomly extracted from the random forest. The model trained with C5.0 was also a decision tree with one CXCL11 (RNA-seq) variable. Although its performance was demonstrated to be inferior to that of the random forest model, simple decision-making models could be more helpful to clinicians in the actual clinical setting. This study did not intend to compare the performance of machine learning methods. Prediction based on the presence or absence of SRC when only histopathological information is available or based on the level of CXCL11 in the presence of RNA-seq information could be simpler and more helpful in the actual clinical setting.This study trained data using a decision model to determine the best model for classification among variables. The random forest is widely used as the most popular method to show strong predictive power. This model also showed far superior predictive performance than the C5.0 decision tree model. The random forest method has been shown to demonstrate excellent predictive power to the trained machine, but it is difficult to intuitively interpret the model for use by clinicians in a clinical setting due to the black box problem. In this random forest model, the ROC curve was used to select the optimal model using the largest value. The final value used for the model was mtry = 1. 4 who overlapped with those in this study. Since there are well-known biomarkers, in whole exome sequencing data, such as tumor mutational burden and MSI, we also tried to use exome sequencing data for comparative analysis with the biomarkers found in this study. However, due to missing data in each case, it was difficult to use a full data set to train the model. To integrate each biomarker and compare their predictive performance, further studies of models trained with a larger number of data sets without missing data are required.One of the difficulties in integrating each data point to train a new biomarker model was the missing data for each case. In this study, 100 cases were subjected to a histopathological evaluation, and 45 cases had RNA-seq data, but only 33 cases had both. We attempted to use the whole exome sequencing data of patients from a previous study conducted by the research team of Professor LeeSupplemental FiguresSupplemental Tables


Nature Communications 10.1038/s41467-021-27155-1, published 25 November 2021.Correction to: E. coli, LIL3 binding to chlorophyll a and LIL3 dimerization. This work should have been cited at the beginning of the fourth paragraph of the Introduction.The original version of this Article omitted references to previous work by Mork-Jansson et al. and Mork-Jansson and Eichacker describing the heterologous expression of LIL3 in 17,18, how the associated pigments are organized and what exactly is the mechanism of binding are long-standing questions”. The corrected version reads “Although LIL3 and ELIP proteins probably bind Chlmolecules in vivo17,18 and the binding of Chl to LIL3 in vitro has been reported19,20, how the associated pigments are organized and what exactly is the mechanism of binding are long-standing questions”.The original sentence stated “Although LIL3 and ELIP proteins probably bind Chl molecules in vivoThese references have been added as reference numbers .In addition, the fourth sentence of the Abstract previously stated “Whether the LHC-like proteins bind pigments has remained unclear”. The corrected version reads “How pigments associated with LHC-like proteins are organised and how they contribute to protein function has not yet been determined”Arabidopsis thaliana. FEBS Lett.589, 3064–3070 (2015).Mork-Jansson, A. E. et al. Lil3 dimerization and chlorophyll binding in PLoS ONE13, e0192228 (2018).Mork-Jansson, A. E. & Eichacker, L. A. Characterization of chlorophyll binding to LIL3. This has been corrected in the PDF and HTML versions of the Article.


Fragaria spp.) is a member of the Rosoideae subfamily in the family Rosaceae. The self-incompatibility (SI) of some diploid species is a key agronomic trait that acts as a basic pollination barrier; however, the genetic mechanism underlying SI control in strawberry remains unclear. Two candidate S-RNases (Sa- and Sb-RNase) identified in the transcriptome of the styles of the self-incompatible Fragaria viridis 42 were confirmed to be SI determinants at the S locus following genotype identification and intraspecific hybridization using selfing progenies. Whole-genome collinearity and RNase T2 family analysis revealed that only an S locus exists in Fragaria; however, none of the compatible species contained S-RNase. Although the results of interspecific hybridization experiments showed that F. viridis (SI) styles could accept pollen from F. mandshurica (self-compatible), the reciprocal cross was incompatible. Sa and Sb-RNase contain large introns, and their noncoding sequences (promotors and introns) can be transcribed into long noncoding RNAs (lncRNAs). Overall, the genus Fragaria exhibits S-RNase-based gametophytic SI, and S-RNase loss occurs at the S locus of compatible germplasms. In addition, a type of SI-independent unilateral incompatibility exists between compatible and incompatible Fragaria species. Furthermore, the large introns and neighboring lncRNAs in S-RNase in Fragaria could offer clues about S-RNase expression strategies.Strawberry ( Incompatibility includes self-incompatibility (SI) and interspecific incompatibility, and it has been demonstrated that both have common genetic factors and share some intermediate mechanisms in Solanaceae8. SI is a type of pollination barrier that serves as a basis for studying other incompatibility mechanisms8. Therefore, the elucidation of the molecular mechanism underlying SI will enable the development of strategies aimed at improving molecular breeding in strawberry.The germplasm of low ploidy wild strawberry contains abundant genetic resources that control valuable traits and is a potential resource for improving cultivated strawberry. However, pollination obstacles between styles and pollen have considerably hampered strawberry breeding9; this process may involve multiple genetic mechanisms. To date, two GSI mechanisms have been identified, including S-RNase-based GSI, identified in Solanaceae, Plantaginaceae, and Rosaceae, and signal transduction GSI, identified in Papaveraceae11. Strawberries belong to the genus Fragaria in the subfamily Rosoideae (family Rosaceae). Although there is broad consensus that the family Rosaceae is divided into three subfamilies , the genetic relationships among the subfamilies remain controversial14. The tribes Maleae  and Amygdaleae (which includes Prunus) in the subfamily Amygdaloideae exhibit S-RNase-based GSI, and its mechanism has been studied extensively. Among them, the genera Malus and Pyrus have similar GSI mechanisms that are distinct from the mechanism in the genus Prunus15. However, little is known about the SI mechanism in the genus Fragaria in the subfamily Rosoideae19.Gametophytic SI (GSI) is a genetic mechanism that inhibits the self-pollination and growth of inbred pollen tubes. The phenotype is determined by the S haplotype of the pollen, which results in the generation of same-genotype pollen tubes that cannot normally extend to the ovary in the styleS-RNase-based GSI system, some self-compatible variants exist in nature17. Recently, increased research on SI has helped unravel the mechanisms by which some mutations exert their effects. The major reasons for the occurrence of self-compatibility (SC) include the sequence loss of key genes21 or the loss of function of S-encoded proteins because of sequence variations at the S locus23. SI requires a certain S-RNase threshold, and the abnormal expression of S-RNase can overcome the SI in a species25. There are some indications that the S intron sequence and S locus methylation level can influence the expression of S-RNase27. Flowering plants of the same species, including strawberry, can exhibit both SI and SC. Unilateral incompatibility (UI) often exists between the two types and is considered to be related to SI28. In addition, the UI observed in SC × SC crosses supports the existence of additional interspecific barriers that are not dependent on SI8. The reasons underlying the compatibility of strawberries have not been elucidated, and to our knowledge, there have been no studies on whether there is a types of UI between SI and SC species in Fragaria that is not associated with S-RNase-based SI.Although Rosaceae members exhibit the Fragaria spp. exhibit SI, with Fragaria viridis, F. nubicola, F. pentaphylla, and F. nipponica exhibiting SI and F. vesca and F. nilgerrensis exhibiting SC31. Bosković et al.6 suggested that there are two unlinked RNase loci that control strawberry incompatibility that are different from the single S locus in Amygdaloideae17. The presence of any locus can result in the specific rejection of cognate pollen, in addition to the nonspecific rejection of pollen with Sn and Tn null allele genotypes. The polypeptides encoded by the two loci are also different from those in the Amygdaloideae subfamily. The above results are based on analyses of style RNase; however, not all RNases expressed in styles are S-RNase18. Therefore, whether there are two S control loci still requires further verification. Similarly, S-RNases that determine the style type in incompatible species of the genus Fragaria need to be explored further.Fragaria exhibits S-RNase-based SI similar to that in the Maleae and Amygdaleae tribes18. In the present study, two S-RNase candidates  were obtained from the style expression database of F. viridis 42. The sequence and expression analysis of the two candidates, the identification of the genotypes of selfing lines, and intraspecific hybridization between different S genotype lines confirmed that Sa and Sb-RNase are alleles and style SI determinants in F. viridis. Expression analysis of S-RNase and the whole-genome identification of the RNase T2 family genes showed that S-RNase was lost in self-compatible strawberry germplasms. Only one S locus was found on chromosome 6 based on collinearity analysis using the F. vesca genome and RNase T2 family genes analysis in F. viridis. Interspecific hybridization revealed a principle inconsistent with the SI × SC rule in Fragaria plants, in addition to having no correlation with the S-RNase genotype. Furthermore, UI was observed between compatible strawberries. In addition, the S-RNase of the genus Fragaria is a very large gene , and the noncoding sequence of the genes (intron and promotor) can transcribe long noncoding RNAs (lncRNAs); these may provide new insights into the mechanism of the regulation of S-RNase expression.It is speculated that the genus S-RNase belongs to Class III in the RNase T2 protein family32. In contrast to non-S-RNase genes, S-RNase, as a candidate SI determinant, has specific characteristics that distinguish it from other RNase genes18. RNase T2 family gene members were screened using HMM, and 14 and 13 genes were screened from the proteome database in F. vesca and F. viridis, respectively. Detailed information about the characteristics of the selected RNase T2 family genes is shown in Table F. viridis were selected, and SC analysis in F. vesca was performed. Flower balls containing styles from wild F. viridis 42 at 0 h and 24 h after self-pollination were selected for transcriptome sequencing and for further use in the establishment of a style proteome database. The basic data used to obtain the proteome data for F. viridis have been submitted to the Sequence Read Archive database. The accession numbers are PRJNA361176, PRJNA361185, PRJNA361192, PRJNA361199, PRJNA361204, and PRJNA361208.34, and 12 and 8 deduced proteins containing signal peptides were obtained from F. vesca and F. viridis, respectively. The functional domain of RNase T2 is a basic structure that contains essential functional units and plays a key role in mediating GSI responses38. We set a domain integrity >60% as the condition for screening S-RNase and further filtered 3 and 1 nonstandard proteins in F. vesca and F. viridis, respectively. The isoelectric point (pI) of S-RNase has been reported to range from 8 to 1040. Based on the pI, three genes were simultaneously eliminated from F. vesca and F. viridis based on the last filtered result. As the number of S-RNase introns does not exceed two41, four proteins were obtained from F. vesca , and four were obtained from F. viridis . S-RNase exhibits a high degree of polymorphism, with amino acid identity ranging from 30 to 90%42. Further identity analysis of the four selected proteins in F. viridis revealed two combinations that satisfied the conditions. The amino acid similarity between Unigene10929.1 and Unigene7320.1 was 56.48%, and that between Unigene23139.1 and Unigene7320.1 was 30.88% . Unigene10929.1 and Unigene7320.1 were confirmed as the RNase T2s linked to the SI phenotype (see the section “Intraspecific hybridization between different S genotype lines of F. viridis”); by extension, there were no eligible S-RNases in F. vesca. In addition, unlike the RNase T2 family genes that were assessed to be non-S-RNases, the position on the chromosome, the number of amino acids, and the amino acid sequence pattern indicated that Unigene10929.1 and Unigene7320.1 are candidate S-RNases41.The presence of a signal peptide is one of the prerequisites for the extracellular secretion of proteinsS-RNases  and a hypervariable region (RHV) .In summary, Unigene10929.1 and Unigene7320.1 conformed to the Sa and Sb-RNase genes were obtained. The partial sequencing results at both ends of the fragments were consistent with the known sequences, so the resulting PCR products were the intended target segments. The first introns of Sa and Sb-RNase were ~15 kb long, and the second introns of Sa and Sb-RNase were ~15 kb and 8 kb long, respectively  corresponded to the first intron of Sb-RNase  of S-RNase (Sa and Sb-RNase), and the cDNA of the flower balls was used as a template. The results showed that Sa and Sb-RNase were expressed only in F. viridis 42, and their expression was not detected in all compatible strawberry germplasms  chromosome 3 and Prunus  genome chromosome 6 with Fragaria (F. vesca) and observed that both rose chromosome 3 and almond genome chromosome 6 had large collinear blocks with F. vesca chromosomes 1 and 6. However, further analysis revealed that the S loci of rose and almond had a common collinear region with F. vesca chromosome 6. In contrast, it had no collinear region with F. vesca chromosome 1 , 3.4 (Chr: 2072839–5489398), and 7.0 (Chr: 3802–7052976) Mb, respectively  in the predicted S locus region. Notably, there were F-box gene clusters near the two RNase T2 family genes . However, these two RNase T2 family genes were not S-RNase genes .The deciphering of plant genomes and the construction of databases has made data mining related to agronomic traits increasingly convenientnes Fig. , which wPyrus plants15, the SI of F. viridis is not complete, and a small number of progenies are derived from seeds contained in malformed fruits through self-pollination. First, a total of 29 lines, including wild F. viridis 42 (zero generation), selfed first generations, selfed second generations, and selfed third generations, were screened for the Sa- and Sb-RNase genotypes using degenerate primers  without the Sa- and Sb-RNase null gene locus lines; therefore, we preliminarily considered Sa- and Sb-RNase as alleles. To further confirm that Sa- and Sb-RNase were alleles, we selected “S1-02-S2-76-S3-09” (SaSb) for self-crossing and obtained 214 progeny lines. The genotype was identified by FSaSb and RSaSb. The genotype ratio was SaSa:SaSb:SbSb = 48:106:60 ≈ 1:2:1. The progeny genotypes of “S1-02-S2-30-S3-09” (SaSa) following selfing were all SaSa, and the progeny genotypes of “S1-02-S2-76-S3-11” (SbSb) following selfing were all SbSb. The progenies of “S1-02-S2-30-S3-09” (SaSa) and “S1-02-S2-76-S3-11” (SbSb) crosses were all SaSb. Sa- and Sb-RNase conformed to the Mendel’s law of segregation, which confirmed that Sa- and Sb-RNase were alleles.Polyacrylamide gel electrophoresis (PAGE) was used to identify nucleotide differences between the two genes, while genomic DNA was used as a template. Similar to that in rs Table . There wSa- and Sb-RNase in F. viridis SI, three genotypes, SaSa, SbSb, and SaSb, were selected to conduct selfing and intraspecific hybridization  was found to be characterized by pollen tube growth patterns similar to those observed after the self-pollination of compatible germplasms. However, when F. nilgerrensis 45, as the female parent, was crossed with F. viridis 42 and F. mandshurica 43, the growth of most pollen tubes was restrained at 1/3–1/2 of the length of the style, and only a small number of uninhibited pollen tubes extended through the bases of the partial styles. In the incompatible interspecific hybridizations—when F. mandshurica 43  was crossed with F. viridis 42 and F. viridis 42  was crossed with F. vesca 41—the growth of most pollen tubes was restricted at 1/3–1/2 of the length of the style. In addition, when F. viridis 42 and F. mandshurica 43  were crossed with F. nilgerrensis 45, the growth of most germinated pollen tubes was considerably inhibited, reaching only 1/5 of the length of the style. We also observed that pollen from F. nilgerrensis 45 exhibited lower germination rates than that from F. vesca 41 and F. viridis 42 on the stigma of F. mandshurica 43 and that the pollen tubes did not pass easily through the stigma.The growth status of the pollen tubes in the styles was investigated at 48 h after self- and cross-pollination, and the results are shown in Fig. 17. Strawberry plants belong to another subfamily, Rosoideae, in the family Rosaceae, and the mechanism of the regulation of incompatibility in this subfamily remains unclear. Based on the results of S genotype identification and cross-pollination experiments, Sa- and Sb-RNase are determinants of SI in the styles of F. viridis, and Sa- and Sb-RNase are alleles of the S locus. Furthermore, the genus Fragaria has an S-RNase-based SI type, which demonstrates the unproven GSI mechanism in Rosoideae and further advances our understanding of the SI system in Rosaceae. These observations are also in agreement with a recently published paper identifying the S-locus in the genus Rosa51. Most pollen tubes are generally suppressed at 1/3–1/2 of the style from the stigma when SI occurs53. Consistent with the results of previous studies45, the SI of Fragaria plants responds relatively slowly to pollen after pollination, implying some differences in the intermediate mechanism or the SI modification factors.Relatively extensive research has been carried out on SI in the subfamily Amygdaloideae  and the tribe Maleae (apple and pear)54. Such compatibility phenomena are relatively widespread in plants of the genus Fragaria, not only in cultivated species but also in many wild species, such as F. vesca, F. nilgerrensis, and F. mandshurica29. Consistent with previous reports, genome-wide RNase T2 family analysis has confirmed that no S-RNase has been observed in self-compatible species18. Further clues about the compatibility of the germplasm in the genus Fragaria were found through collinearity analyses. Two RNase T2 family genes were present at the identified S locus; however, the two genes did not conform to the characteristics of S-RNase. The conversion of a self-incompatible germplasm into a self-compatible germplasm often occurs in Rosaceae, typically due to variations in the genome sequence that result in the loss of gene fragments or gene functions of S determinants in the style or pollen58. Our results suggest that S-RNase was lost at the S locus of self-compatible germplasms during evolution.Notably, there are some self-compatible germplasms in the Rosaceae family with SI systemsS-RNase is expressed specifically in the styles and is maintained at higher levels after self-pollination, which is very important for the development of the SI phenotype25. However, few reports have explored the regulation of S-RNase expression, and only the promotor of S-RNase has been identified60. The self-incompatible S locus is located at the centromere (Solanaceae) or subtelomeric position on the chromosome. The region is often hypermethylated61, highly repetitive in its sequence, and heterochromatised62; these properties may make the DNA conservative and difficult to recombine and, in turn, restrict gene expression64. Fernández i Marti et al.27 showed that the methylation of the S locus in almonds is related to the loss of S-RNase function. In addition, the roles of introns in expression regulation have also been increasingly reported65. S-RNase in the genus Fragaria has a large intron and is currently the longest S gene; these characteristics are also rare in plant genes. However, whether such large introns are also involved in gene expression regulation requires further investigation. Some noncoding sequences can be expressed and play important roles in gene regulation67. Here, we detected the existence of related adjacent long noncoding RNAs near S-RNase, including the promotor and intron regions, which also provide further new clues for S-RNase expression regulation. All of these findings indicate the complexity of S-RNase expression regulation, which may involve multiple processes. However, much research work is still needed to clarify its mechanism.7. Among the three interspecific hybridizations between F. viridis and F. vesca, F. mandshurica, and F. nilgerrensis, two hybridizations conformed to the rule above and were consistent with previous research results, suggesting that the UI is related to the S-RNase-based SI68. However, when F. viridis was crossed with F. mandshurica, the result was contrary to the SI × SC rule and was not influenced by the S genotype  but also between SI and SC germplasms (such as F. viridis and F. mandshurica)  Fig. . The disSolanum and Pyrus, cross-compatible pollen tubes can reach the base of the style, and some even pass through the style bottom. However, interspecific incompatible pollen tubes often stop growing within 1/3 of the length of the style52. In Solanum, interspecific incompatible pollen tubes are arrested earlier than self-incompatible pollen tubes7; a similar phenotype was also observed in Fragaria. There were also some differences in the inhibition time between different interspecific hybridizations in Fragaria plants. Some interincompatible pollen tubes (1/3–1/2) in Fragaria are suppressed later than those in Solanaceae7 (within 1/3 of the length of the style); however, some interspecific hybridizations are stopped earlier. Consistent with previous results, F. vesca accepts pollen from other strawberry species relatively easily31. In the present study, F. nilgerrensis had a lower capacity to accept pollen from germplasms other than F. vesca, and the intensity of pollen suppression was greater in the pistils of other germplasms. The functional structural units involved in incompatibility include the pistil-side barrier and pollen-side resistance. Additionally, incompatibility occurs when pollen resistance is lacking or is weaker than the pistil-side barrier71. The interspecific hybridization barrier is also a relatively primitive state that prevents gene exchanges among related germplasms72. We speculate that when the pistil-side barrier in F. vesca weakened, the style of F. nilgerrensis maintained a certain capacity to overcome pollen resistance, and the pollen developed relatively weak resistance during evolution. These results explain why F. vesca is a reasonable candidate intermediate germplasm for gene exchange and why F. nilgerrensis 45, in a compatible interspecific hybridization, hinders most of the pollen tubes of F. viridis and F. mandshurica. They also explain why the pollen tubes of F. nilgerrensis are strongly restricted in the styles of F. viridis and F. mandshurica in incompatible interspecific hybridizations. Moreover, the phylogenetic evolution of Fragaria shows that F. nilgerrens has a distant relationship with F. viridis and F. mandshurica73. Thus, the influence of phylogenetic distance on the compatibility of interspecific hybrids cannot be ruled out.In other genera, including 6 hypothesized that two RNase loci (S and T) can explain the regular occurrence of SI and UI in the genus Fragaria. However, this hypothesis—that SI is controlled by S-RNase—is constrained by the fact that not all style-expressed RNases are S-RNases74. Sequence information for these two loci has not been obtained. In addition, peptide sequences that have been previously used to demonstrate that the S and T loci encode RNase proteins are controversial18. In contrast to previous findings, only two allelic S-RNases could be identified using the deduced style protein database of F. viridis based on information regarding the characteristics of S-RNase, and the two genes were identified as style SI determinants using the hybridization experiment; these findings indicate that only one S locus plays a role in SI in the genus Fragaria. Based on genome-wide collinearity analysis, the S locus regions of the almond and rose genomes had only one collinear region with the F. vesca genome, on chromosome 6 (Chr6: 2792689–5489398). Pgl1 exists in this region , F. nilgerrensis 45 (SC), F. mandshurica 43 (SC), and F.× ananassa “Benihoppe” (SC) for an analysis of the expression of S-RNase using RT-PCR. This was accompanied by cross-pollination experiments among four wild germplasms to further analyze the role played by S-RNase in the interspecific hybridization of the genus Fragaria. All resources used in the experiments were stored at the Baima Teaching and Research Base of Nanjing Agricultural University in Baima Town, Nanjing City, Jiangsu Province, China. Strawberry resources grown in the field (from March 2019 to June 2019) were used for selfing, cross-pollination, and sample collection. The temperature during this period was suitable for strawberry growth and enabled the plant materials to bloom normally. In addition, the flowering periods of the four Fragaria species partially overlapped. Various flowering stages differentially influence pollination results; therefore, we specifically selected flowers at the large bud stage (C3–C5) .A total of six biological samples—three http://hmmer.org/download.html)76 was used to search the genomic protein database of F. vesca and F. viridis to obtain the RNase T2 and F-box gene family members. To verify the integrity of the protein domains and filter out proteins that did not contain RNase T2 domains, the selected proteins were checked using the National Centre for Biotechnology Information (NCBI) Conserved Domains Database (https://www.ncbi.nlm.nih.gov/cdd/?term). The molecular weight and isoelectric point of the obtained RNase T2 family members were analyzed by ExPaSy (https://web.expasy.org/protparam/)77, and the signal peptides were analyzed by SignalP 78. Meanwhile, alignment analysis of the amino acid sequence was performed using DNAMAN8.0 .According to the hidden Markov model (HMM) of RNase T2 and the F-box domain, the hmmsearch program in Hmmer software (http://pfam.xfam.org/), and the other is by constructing an RNase T2 HMM using a known S-RNase  in the search window of the NCBI database. According to the annotations, some genes with unclear functions or incomplete sequences were omitted from the analysis, and the more reliable S-RNase genes, which were recognized S-RNase family members  directly from the Pfam database (F. vesca were downloaded from the Genome Database for Rosaceae (https://www.rosaceae.org/), and the F. vesca genome v 4.0.a1 was used. The F. viridis style proteome was predicted based on the style transcriptome (Supplementary Dataset 79 was used to predict the open reading frames (ORFs)  was used to improve the display of the evolutionary tree as well as to add group labels and colors. According to the results of the evolutionary analysis, the species closely related to the candidate S-RNases of F. viridis were selected in order to analyze the conservative structure of the candidates.The F. viridis 42  was used to reverse transcribe the RNA into cDNA, according to the manufacturer’s instructions. After reverse transcription, the appropriate amount of ddH2O was added to dilute the mixture to 200 ng/µL based on the desired concentration. Specific primers were designed  was used in the reaction. The amplification procedure for the Sa-RNase was as follows: 1 cycle (98 °C for 5 min), 36 cycles , a final extension at 68 °C for 10 min, and storage at 10 °C. The annealing temperature of Sb-RNase was 53 °C. The temperature conditions for the other reactions were similar to those described above. The PCR products obtained after the addition of a base (A) at both ends of the obtained flat-end sequences were analyzed on 1.5% agarose gels, and the putative fragments were purified using a DNA purification kit . The procedure for adding the “A” base was conducted at 72 °C for 30 min using rTaq . The purified fragment was cloned into the pMDTM19-T vector  and transformed into E. coli DH5α competent cells . Ten monoclones per gene were sequenced by a biotechnology company . The sequence obtained was compared with the sequence from the transcriptome using DNAMAN v8.0 .RNA was extracted from the flower balls containing the styles of S-RNase. This indicated that S-RNase may contain large introns. To obtain genetic information regarding S-RNase, the nucleotide sequences of S-RNase were first analyzed to identify the exon-intron structure of the gene. Then, specific primers against the intron were designed at the intron-exon boundary of the gene using the segmented cloning approach. The GXL enzyme was employed to amplify the target fragment using a rapid reaction program. The annealing temperature was 60 °C, and the extension time was 1 min and 50 s. Fresh young leaves of F. viridis were collected and stored at −80 °C in an ultralow-temperature refrigerator after quick freezing in liquid nitrogen. gDNA was extracted using the Super Plant Genomic DNA Kit , which is suitable for plants with high polysaccharide and polyphenolic contents. The following steps were used to design primers for S-RNase cloning: (1) the quality of the original reads (paired-end sequences) obtained from whole-genome resequencing data45 of Ls-S2-53 was evaluated and filtered to obtain clean reads; (2). SOAPdenovo 282 was used to assemble clean reads that were not mapped to the reference genome, and a series of contigs and scaffolds were obtained as the database sequences; (3) Sa and Sb-RNase transcripts representing query sequences were aligned with database sequences, and the boundaries of introns and exons were defined by analyzing the alignment results between S-RNase and its matched genome splicing sequence; and 4) after clarifying the number and positions of introns, upstream and downstream primers were designed against the first exon and the second exon or their matching sequences (contigs and scaffolds) and were used to clone the first intron; additional primers were designed against the second exon and the third exon or their matching sequences in order to clone the second intron. The primers used to clone the first and second introns of Sa-RNase were FSaIntron1 and RSaIntron1 and FSaIntron2 and RSaIntron2, respectively. The primers used to clone the first intron of Sb-RNase were FSbIntron1 and RSbIntron1, and those used to clone the second intron were FSbIntron2 and RSbIntron2. The primer sequences are listed in Supplementary Table The target PCR product could not be obtained from the genome using cloning primers designed with the full-length CDS of Sa- and Sb-RNase and style cDNA after 12 h of self-pollination (template), the genotypes of the materials were determined  was used in combination with degenerate primers FSaSb and RSaSb in the PCR. The amplification procedure was as follows: 95 °C for 5 min and 36 cycles , a final extension step at 72 °C for 5 min, and storage at 10 °C. The PCR product was diluted 10 times, and 2 µL was examined after staining with bromophenol blue in a 10% polyacrylamide gel for electrophoresis. The running procedure was as follows: 90 v pre-electrophoresis for 15 min, 160 v electrophoresis for 1.5 h, pause for 30 min, and 160 v electrophoresis again for 1.5 h. The polyacrylamide gel was soaked in silver staining solution (1 g AgNO3 + 33 mL C2H5OH + 3 mL CH3COOH + 750 mL ddH2O) for 15 min and then soaked in a developer solution (10 g NaOH + 4.5 mL HCHO + 750 mL H2O) for more than 10 min after twice cleaning with ddH2O and subsequently photographed under white light. In addition to the selfing lines in Table Using specific primers against the CDS (full-length) of F. viridis 42 as the control, S-RNase expression in compatible strawberry species, such as F. vesca 41, F. nilgerrensis 45, F. mandshurica 43, and F.× ananassa “Benihoppe”, was tested. Total RNA was extracted from the flower balls, and cDNA was synthesized for S-RNase expression detection. The detection primers were specific primers used to clone the full CDS of Sa and Sb-RNase and their degenerate primers. At the same time, the styles, ovaries, and receptacles of the flower balls, as well as the petals, calyxes, pedicels, leaves, and anthers, were collected for tissue-specific expression analysis of Sa- and Sb-RNase. Taking the unpollinated flower balls as the control, spatiotemporal expression analysis of S-RNase after pollination was performed at 6 h, 12 h, 18 h, and 24 h. The expression analysis of S-RNase in a different germplasm and different tissues was performed using RT-PCR, while spatiotemporal expression analysis was performed using qRT-PCR. The RT-PCR is detailed in the section “Cloning and sequence analysis of Sa-RNase and Sb-RNase”, and the qRT-PCR method is detailed here. First, the synthesized cDNA was diluted to 100 ng/µL using SYBR Premix Ex TaqTM (TaKaRa), and then an ABi 7500 fluorescent quantitative PCR system  was used to perform qRT-PCR. The internal reference primer was the elongation factor-α gene EF1-α. Each reaction consisted of a 20 µL volume containing 10.0 µL SYBR Premix Ex TaqTM (TaKaRa), 1 µL cDNA, 0.5 µL of each primer (10 µM), and 8 µL ddH2O. The reaction conditions were as follows: 95 °C for 4 min and 40 cycles . The upstream and downstream primers were designed on the basis of the second and third exons of S-RNase, respectively. The primer pairs used to detect Sa-RNase were FSak and RSak, and RSbk and FSbk were used to detect Sb-RNase  were selected for artificial emasculation and isolated using pollination bags in the afternoon. On the following morning, starting at 9 am, artificial pollination was performed, and the flowers were isolated again. Generally, pollen with good germination capability, as determined using pollen activity tests, is used in pollination experiments. The pollen germination medium was slightly modified based on a previous methodF. viridis lines were selected for use in the intraspecific pollination experiments for each S genotype, and one line from the different S genotypes was selected for use in the interspecific pollination experiments. In the interspecific hybridizations, all germplasms were self-compatible, excluding that of F. viridis. The flowering times of the different germplasms were slightly different, and the rate of development of the receptacle also varied across the germplasms. Typically, photographs of the fruit were taken 15–25 d after pollination, and the fruit-set rate following the interspecific hybridizations was determined; however, the seed-set rate of single fruits was determined after fruit maturity. In addition, for the intraspecific hybridization of F. viridis, mutual pollination was performed with blooming flowers of different S-genotype lines using the smearing method without the influence of external pollinators in the greenhouse, and the development and color changes of the receptacles and achenes were observed within 10 d of pollination.Receptacle development was observed, and the fruit-set and seed-set rates of single fruits were determined after 25 d via intraspecific pollination experiments. In addition, the (in)compatibility of different pollination hybridizations was analyzed by examining the overall growth status of the pollen tubes in the different styles. Three F. vesca and rose and almond genomes as well as between the two rose genomes using BLAST, while MCScanX83 and Ciros (http://circos.ca/) were used to illustrate collinearity. The genomes and the associated versions used were as follows: F. vesca genome v4.0.a184, Rosa chinensis genome v1.0 (Rosa_v1)49, Rosa chinensis “Old Blush” homozygous genome v2.0 (Rosa_v2)85, and P. dulcis “Texas” genome v2.0. The chromosomes harboring the S locus in almond and rose were used to further analyze collinearity with the whole genome of F. vesca to obtain the collinearity blocks distributed in F. vesca. Furthermore, based on whether the collinearity blocks in F. vesca exhibited collinearity with the S locus of almond and rose, the numbers and positions of the S loci in the genome of Fragaria were further determined. Based on the location of S-RNase in the reported almond genome, Rosa_v1 rose genome49, and the evaluated Rosa_v2 rose genome (Supplementary Fig. S loci areas were obtained by extending the 3’ and 5’ termini of S-RNase by ~2.5 Mbp. The F. vesca genome regions that exhibited collinearity with the S locus of the almond genome, Rosa_v1 rose genome, and Rosa_v2 rose genome were selected to perform a more accurate location analysis. The reason for compatibility in strawberry was further determined through a functional analysis of RNase T2 family members and the distribution of F-box family members at this locus.Genome-wide collinearity analysis was performed between the Supplementary Figures S1-S13, Tables S1-S7 and Sequence S1-S2Dataset S1Dataset S2Dataset S3Dataset S4


Gsdmd wild-type SAP mouse models, Gsdmd knockout (–/–Gsdmd) ameliorated SAP-induced pancreas and related lung injury. Additionally, we investigated the effects of disulfiram on the treatment of SAP. Disulfiram is a Food and Drug Administration (FDA)-approved anti-alcoholism drug, which is reported as an effective pyroptosis inhibitor by either directly covalently modifying GSDMD or indirectly inhibiting the cleavage of GSDMD via inactivating Nod-like receptor protein 3 inflammasome. We demonstrated that disulfiram inhibited the cleavage of GSDMD, alleviated caerulein-induced SAP and related lung injury, and decreased the expression levels of proinflammatory cytokines (IL-1β and IL-18). Collectively, these findings disclosed the role of GSDMD-mediated pyroptosis in SAP and the potential application of disulfiram in the treatment of SAP.The functional relevance and effects of the pyroptosis executioner gasdermin D (GSDMD) on severe acute pancreatitis (SAP)-associated lung injury are unclear. We established caerulein-induced mouse models of SAP-associated lung injury, which showed that GSDMD-mediated pyroptosis was activated in both pancreatic and lung tissues. Compared with  Acute pancreatitis (AP) is an inflammatory disorder featured by the destruction of acinar cells. Mostly, AP is mild and self-limited. However, approximately over 20% of all patients with AP will develop to be a severe condition with multiorgan dysfunction, such as the lungs, kidneys, heart, and gut , which rPyroptosis is the inflammasome-induced programmed cell death mediated by gasdermins , which iGsdmd, an import member of the gasdermin family) knockout mice were used. Additionally, the therapeutic effect of disulfiram [DSF, a Food and Drug Administration (FDA)-approved anti-alcoholism drug, is an effective pyroptosis inhibitor by either directly covalently modifying GSDMD or indirectly inhibiting the cleavage of GSDMD via inactivating Nod-like receptor protein 3 (NLRP3) inflammasome  and gasdermin D  mice were a gift from Prof. Feng Shao  . , China) .Gsdmd–/– mice were randomly assigned to the following four groups: (1) WT-sham group, 0.9% saline, intraperitoneal (i.p.) injection; (2) WT-SAP group; (3) Gsdmd–/– sham group; and (4) Gsdmd–/– SAP group. The SAP model was established according to previous studies  on the treatment of SAP, male WT mice were randomly assigned to the following six groups: (1) the sham group, in which the mice received normal saline ; (2) DSF group ; (3) the SAP group; (4) SAP + DSF ; (5) SAP + DSF ; and (6) SAP + DSF . Briefly, mice were pretreated with DSF  24 h before injection of caerulein, and 24 and 4 h before injection of LPS, retrospectively. The timeframe of DSF injection is displayed in All animals were anesthetized via i.p. injection of pentobarbital sodium  (50 mg/kg) and then killed 24 h after the last injection.Blood samples were collected by eye enucleation. After centrifugation, the serum was collected and stored at −80°C for further ELISA analysis. The pancreases and left lungs were enucleated. One part was frozen at −80°C, and the other part was fixed in paraformaldehyde and then embedded in paraffin.The right lung was enucleated, the surface water was absorbed with a filter paper, and then the weight was measured and recorded as the wet weight. After that, the lung was then dried at 70°C in an oven for 48 h, and the dry weight was measured. The wet/dry ratio was calculated.Serum amylase , lipase , IL-1β , IL-18 , IL-6 , and tumor necrosis factor-alpha (TNF-α)  were detected using ELISA kits according to the manufacturer’s instructions.Paraffin-embedded slides of the pancreatic and lung tissues were stained with H&E and then observed under a light microscope. The pancreatic pathology was evaluated according to Schmidt’s criteria . The lun2O2 for 10 min. Antigen retrieval was performed via incubating the slides in 0.1% trypsin and heating them in a microwave oven. The slides were incubated with primary antibodies (1:200 dilution) at 4°C overnight, with the primary antibodies including anti-IL-1β  (1:200) and anti-IL-18  (1:200). Then, the slides were incubated with horseradish peroxidase (HRP)-conjugated secondary antibody (1:200) for 30 min at 37°C. Diaminobenzidine (DAB) used as a chromogen. The slides were counterstained with hematoxylin.The slides were deparaffinized in xylene and rehydrated in a graded ethanol series. Endogenous peroxidase activity was blocked with 3% HThe slides were prepared and covered with 1% bovine serum albumin in phosphate-buffered saline (PBS). Slides were incubated overnight at 4°C with primary antibodies to IL-1β (1:300) and IL-18 (1:300) and then washed and incubated with the secondary antibody for 2 h at room temperature in the dark. After washing, the slides were stained with 4′,6-diamidino-2-phenylindole (DAPI)  and visualized with a fluorescence microscope.Total protein was isolated from the pancreatic and lung tissues. The concentrations were measured by bicinchoninic acid assay. Protein samples were loaded and separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis and then transferred to a polyvinylidene difluoride membrane . The membrane was blocked with 5% skimmed milk at room temperature for 1 h and then incubated with primary antibodies to IL-1β , IL-18 , and GSDMD   overnight at 4°C. The membrane was washed and then incubated with secondary antibodies   at room temperature for 1 h. Finally, the protein bands were scanned with echochemiluminescence detection system and quantified using Image-Pro Plus 6.0 software .t-test for two groups or two-way ANOVA for multiple groups. p-values were provided as ∗p < 0.05 and #p < 0.05.Data were collected and analyzed by GraphPad Prism 7.0 software and presented as the means ± SD. The statistics were analyzed by using two-tailed unpaired Gsdmd knockout decreased the levels of IL-1β and IL-18 in pancreatic tissues and serum  and 10 members in mice . pathway . The N-t pathway .Gsdmd–/– mice increased protection on caerulein-induced AP.GSDMD is a 53-kDa protein and is extensively investigated in pyroptosis. Only few studies reported the involvement of GSDMD-mediated pyroptosis in the pathogenesis of AP. Pyroptosis is involved in the progression of SAP-associated ALI. Activation of NLRP3 inflammasome-dependent pyroptosis in alveolar macrophages (AMs) was responsible for the lung injury secondary to SAP. Plasma-derived exosomes from SAP mice were capable of triggering NLRP3-dependent pyroptosis in AMs . Emodin DSF is an FDA-approved anti-alcoholism drug. As early as 2008, Kast proposed the potential therapeutic value of DSF on AP based on the relationship between IL-18 and AP , yet ourIn conclusion, we reported on GSDMD-mediated pyroptosis involved in the progression of SAP-associated ALI. Targeted therapy of GSDMD using DSF inhibited pyroptosis and alleviated the injury of the pancreas and lung.The original contributions presented in the study are included in the article/The animal study was reviewed and approved by Medical Ethics Committee of Qilu Hospital of Shandong University.JX performed the study concept and design. JW and JX performed the development of methodology and the writing, review, and revision of the manuscript. JW, JTZ, and JPZ provided the analysis, interpretation of data, and the statistical analysis. JX, JW, JTZ, SC, and TZ provided the technical and material support. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The M-SIA was 1.12 ± 0.55 D, and the C-SIA was 0.73 D @64° ± 1.02 D in the right eye group, and the M-SIA was 1.08 ± 0.48 D and the C-SIA was 0.60 D @117° ± 1.03 D in the left eye group. The C-SIA showed an astigmatic shift toward the nasal-superior location of the scleral flap creation. Our results revealed that trabeculectomy induced the SIA in the direction of the scleral flap location and that the C-SIA was much lower than the M-SIA in eyes undergoing trabeculectomy.This study aimed to investigate the arithmetic mean of surgically induced astigmatism (M-SIA) and the centroid of surgically induced astigmatism (C-SIA) after standard trabeculectomy. We comprised 185 eyes of 143 consecutive patients  who underwent trabeculectomy and completed at least a 3-month routine follow-up. In all cases, the scleral flap was made at the nasal-superior location. Corneal astigmatism was measured with an automated keratometer. We calculated the M-SIA and the C-SIA using vector analysis and applied the astigmatism double angle plot. The magnitude of corneal astigmatism increased significantly, from 1.17 ± 0.92 D preoperatively to 1.77 ± 1.05 D postoperatively (paired  Glaucoma surgery is currently performed to lower the intraocular pressure (IOP) since high IOP is a major risk factor for glaucoma progression ,2, and lCurrently, two analytic methods are available for SIA measurements in a clinical setting; the arithmetic mean of SIA (M-SIA) is calculated based on the mere magnitude of astigmatism, whereas the centroid of SIA (C-SIA) is calculated based on the magnitude, as well as the direction of astigmatism. Until now, several studies have been conducted on SIA outcomes after trabeculectomy, but most studies have merely focused on the M-SIA with a small cohort of such patients. Considering that the C-SIA was clinically helpful for grasping the overall trends of SIA, it may give us intrinsic insights on planning a preoperative strategy for reducing astigmatism in patients requiring trabeculectomy. Moreover, it is still difficult to accurately grasp SIA trends when using bilateral SIA data, since the scleral flap was made at different positions between the right and left eyes. The goal of the present study is to unilaterally evaluate both the M-SIA and the C-SIA in a large cohort of glaucoma patients undergoing standard trabeculectomy.This study was approved by the Research Ethics Committee of Kitasato University Hospital (B21-070) and registered with the University Hospital Medical Information Network Clinical Trial Registry (000045194). This retrospective review of the clinical charts was performed in accordance with the tenets of the Declaration of Helsinki. This study was carried out with explanations provided to the patients and a poster was displayed with additional information, including an opt out clause. Written informed consent for trabeculectomy was obtained from all patients after explaining the nature and possible consequences of the surgery. Our study comprised a total of one hundred eighty-five eyes of 143 consecutive patients (86 men and 57 women), who underwent standard trabeculectomy for the first time for glaucoma (primary open-angle glaucoma (POAG); 120 eyes and normal-tension glaucoma (NTG); 65 eyes), and who completed at least a 3-month follow-up. We excluded eyes with irregular corneal astigmatism, eyes with poor fixation at the time of preoperative or postoperative examination, or eyes requiring additional interventions, except for suture lyses by the argon laser, from the study. Fifty age- and gender-matched ophthalmologically healthy eyes were used as a control group.2 (square) on the nasal-superior side through a fornix-based conjunctival incision in all cases. We unified the flap location in the 1 and 11 o’clock positions in the right and left eye groups, respectively. Afterward, 0.05% mitomycin C was applied for 3 min. A scleral window of approximately 2.0 × 0.5 mm2 (square) was created using a straight knife and small scissors. After peripheral iridectomy, the scleral flap was sutured with 4 10-0 nylon sutures. Continuous 10-0 nylon sutures were placed on the radial incision, interrupted sutures, and compression sutures were placed on the corneal limbus. If the achieved IOP exceeded the targeted IOP, laser suture lysis was performed as needed. Scleral flap suture lysis was performed by the argon laser based on the targeted and achieved IOP levels during the early postoperative period.All surgeries were performed by two experienced surgeons (MK and NS) at Kitasato University Hospital. The scleral flap was created with a single half-thickness flap of approximately 3 × 3 mmhttps://ascrs.org/tools/astigmatism-double-angle-plot-tool (accessed on 31 October 2021)) ) was −0.01 ± 0.14 D (−0.30 to 0.27 D) for corneal astigmatism .In the present study, our results showed that standard trabeculectomy significantly increased corneal astigmatism by approximately 0.6 D and that the surgery induced the M-SIA and the C-SIA by approximately 1.1 D and 0.7 D in the right eye group, and 1.1 D and 0.6 D in the left eye group, respectively. Our results also showed a significant correlation of the M-SIA with the preoperative corneal astigmatism, but not with the preoperative IOP, suggesting that preoperative corneal astigmatism might play a major role in the M-SIA after trabeculectomy, rather than the preoperative IOP. We assume that unilateral data analysis is more relevant and reasonable than bilateral analysis for the assessment of the actual SIA in daily practice. To the best of our knowledge, this is the first study to unilaterally demonstrate the magnitude and the direction of SIA in a large cohort of patients undergoing trabeculectomy. It has been reported that standard cataract surgery through a 3 mm corneal incision caused a M-SIA of approximately 0.5 D ,11,12,13Although the exact mechanism of SIA remains unclear, several possible explanations for SIA after trabeculectomy have so far been advocated, including tissue removal under the scleral flap , the mecThere are at least two limitations to this study. Firstly, this study was performed in a retrospective fashion. Secondly, we applied an automated keratometer to assess corneal astigmatism, since it is most widely used in daily practice. Accordingly, we did not evaluate the amplitude of posterior corneal astigmatism in this study. It has been demonstrated that the magnitude of posterior corneal astigmatism (approximately 0.30 to 0.35 D) is far smaller than that of anterior corneal astigmatism, and the axis orientation of posterior corneal astigmatism was constant (ATR astigmatism) in most eyes ,29,30, aIn summary, our findings showed that trabeculectomy significantly increased the SIA in the direction of the scleral flap location in both eye groups and that the C-SIA was much smaller than the M-SIA, even after trabeculectomy. We believe that this information will be simple, but clinically beneficial, not only for reducing the amplitude of astigmatism but also for the preoperative planning of astigmatic correction in eyes undergoing trabeculectomy in advanced glaucoma patients.